Slow Sleep Spindles Research Articles

Brain activations time locked to slow wave-coupled sleep spindles correlates with intellectual abilities.

Sleep spindles (SP) are one of the few known electrophysiological neuronal biomarkers of interindividual differences in cognitive abilities and aptitudes. Recent simultaneous electroencephalography with functional magnetic resonance imaging (EEG-fMRI) studies suggest that the magnitude of the activation of brain regions recruited during spontaneous spindle events is specifically related to Reasoning abilities. However, it is not known if the relationship with cognitive abilities differs between uncoupled spindles, uncoupled slow waves (SW), and coupled SW-SP complexes, nor have the functional-neuroanatomical substrates that support this relationship been identified. Here, we investigated the functional significance of activation of brain areas recruited during SW-coupled spindles, uncoupled spindles, and uncoupled slow waves. We hypothesize that brain activations time locked to SW-coupled spindle complexes will be primarily associated to Reasoning abilities, especially in subcortical areas. Our results provide direct evidence that the relationship between Reasoning abilities and sleep spindles depends on spindle coupling status. Specifically, we found that the putamen and thalamus, recruited during coupled SW-SP events were positively correlated with Reasoning abilities. In addition, we found a negative association between Reasoning abilities and hippocampal activation time-locked to uncoupled SWs that might reflect a refractory mechanism in the absence of new, intensive hippocampal-dependent memory processing.

Analysis of slow and fast sleep spindle properties in Parkinson's disease – A comparative EEG study

Study objectivesSleep disturbances and altered sleep macrostructure are common in Parkinson's disease (PD). Few studies have addressed the changes in sleep spindle (SS) properties in this movement disorder so far. SS seem to be fundamental of both sleep architecture and memory consolidation. The aim of our comparative study was to investigate the changes of SS characteristics in PD, and reveal the relationship between SS properties and cognitive function. MethodsWe investigated 20 PD patients and 18 age-matched controls. All participants underwent a 24-hour-long polygraphic EEG recording after extensive clinical investigation. We detected slow and fast SS properties automatically using individual adjusting method (IAM). The data were statistically evaluated. ResultsWe found significantly lower fast spindle amplitude in PD comparing with controls. We did not find significant differences in SS densities, duration and oscillatory frequency between the groups. We detected significant positive correlation between fast SS amplitude and memory in PD, and between fast SS density and retrograde memory in controls. The total Addenbrooke's cognitive score correlated negatively with slow SS density and duration in controls. ConclusionsBy the time clinical diagnosis of PD is established, the pathological process is already spreading. Changes in sleep macrostructure and SS properties might become a useful biomarker of the neurodegenerative process in PD. In addition, decreased fast SS amplitude might predict further cognitive deterioration and indicate early involvement of corresponding cortical area. Our study results strengthen the importance of EEG examination in PD, and the use of IAM method in SS analysis.

Correlating electroconvulsive therapy response to electroencephalographic markers: Study protocol.

Electroconvulsive therapy (ECT) is an effective intervention for patients with major depressive disorder (MDD). Despite longstanding use, the underlying mechanisms of ECT are unknown, and there are no objective prognostic biomarkers that are routinely used for ECT response. Two electroencephalographic (EEG) markers, sleep slow waves and sleep spindles, could address these needs. Both sleep microstructure EEG markers are associated with synaptic plasticity, implicated in memory consolidation, and have reduced expression in depressed individuals. We hypothesize that ECT alleviates depression through enhanced expression of sleep slow waves and sleep spindles, thereby facilitating synaptic reconfiguration in pathologic neural circuits. Correlating ECT Response to EEG Markers (CET-REM) is a single-center, prospective, observational investigation. Wireless wearable headbands with dry EEG electrodes will be utilized for at-home unattended sleep studies to allow calculation of quantitative measures of sleep slow waves (EEG SWA, 0.5-4 Hz power) and sleep spindles (density in number/minute). High-density EEG data will be acquired during ECT to quantify seizure markers. This innovative study focuses on the longitudinal relationships of sleep microstructure and ECT seizure markers over the treatment course. We anticipate that the results from this study will improve our understanding of ECT.

A questionnaire measure of adult attachment anxiety correlates with frontal hemispheric asymmetry in sleep spindle activity

Subjects with high levels of attachment anxiety and neuroticism were proposed to be characterized by higher relative right rather than left frontal activity. Since sleep spindles are argued to reflect enhanced offline neuroplasticity, higher spindle activity measured over the right frontal areas relative to the corresponding left frontal ones could index higher attachment anxiety and neuroticism. Our aim was to explore the relationship between the lateralization patterns of frontally dominant slow sleep spindles and questionnaire measures of adult attachment anxiety and neuroticism. Thirty-four healthy subjects (male = 19; Mage = 31.64; SDage = 9.5) were enrolled in our preliminary study. Second night EEG/polysomnography records and questionnaire measures of personality (Zuckerman–Kuhlman Personality Questionnaire) and adult attachment (Relationship Scales Questionnaire) were collected. Frontal slow sleep spindles were measured by the Individual Adjustment Method (IAM), whereas hemispheric asymmetry indexes of spindle occurrence rate, duration, and amplitude were derived as normalized left–right differences (electrode pairs: Fp1–Fp2, F3–F4, and F7–F8). Relative right lateralization of frontolateral and frontopolar slow sleep spindle density and mid-frontal slow spindle duration were associated with attachment anxiety, but spindle lateralization was less closely related to neuroticism. The relationships between frontal slow spindle laterality and attachment anxiety remained statistically significant even after controlling for the effect of neuroticism, whereas attachment avoidance–independence was not correlated with frontal slow spindle lateralization. Right frontal lateralization of slow sleep spindle activity might indicate attachment status in terms of the negative view of the self.

New Electrographic Marker? Evaluation of Sleep Spindles in Children with Attention Deficit Hyperactivity Disorder.

Introduction: Attention deficit and hyperactivity disorder (ADHD) is one of the most common developmental disorders in childhood which lasts lifelong. Sleep structure and sleep spindle features are disorganized in ADHD. In this study, we aimed to look for a new, simple, inexpensive, and an easily detectable electrographic marker in the diagnosis of ADHD by using electroencephalography (EEG). Method: We included treatment free 35 patients with ADHD and 32 healthy children (HC) who were examined by polysomnography (PSG) and EEG for sleep disorders. The ADHD group were separated into three groups according to predominant presentations of ADHD. We determined the sleep staging and slow and fast sleep spindles, calculated each spindle's amplitude, frequency, activity, duration and density at non rapid eye movement (REM) sleep stage 2. Results: Slow sleep spindle's amplitude, duration, density and activity are significantly higher in ADHD group (most significant in ADHD-I) than the HC group (p < 0,05). Sleep spindle's features are not statistically significant between in ADHD subgroups. Conclusions: In children with ADHD, slow sleep spindles showed higher amplitude, activity, density and duration in the frontal regions. These results indicate that slow sleep spindles in children with ADHD may reflect executive dysfunction and slow frontal spindles may be useful as a new electrographic marker in children with ADHD. This is the first study of its kind evaluating all aspects of sleep spindles in ADHD patients.

The human thalamus orchestrates neocortical oscillations during NREM sleep

A hallmark of non-rapid eye movement sleep is the coordinated interplay of slow oscillations (SOs) and sleep spindles. Traditionally, a cortico-thalamo-cortical loop is suggested to coordinate these rhythms: neocortically-generated SOs trigger spindles in the thalamus that are projected back to neocortex. Here, we used intrathalamic recordings from human epilepsy patients to test this canonical interplay. We show that SOs in the anterior thalamus precede neocortical SOs (peak −50 ms), whereas concurrently-recorded SOs in the mediodorsal thalamus are led by neocortical SOs (peak +50 ms). Sleep spindles, detected in both thalamic nuclei, preceded their neocortical counterparts (peak −100 ms) and were initiated during early phases of thalamic SOs. Our findings indicate an active role of the anterior thalamus in organizing sleep rhythms in the neocortex and highlight the functional diversity of thalamic nuclei in humans. The thalamic coordination of sleep oscillations could have broad implications for the mechanisms underlying memory consolidation.

Mutual interaction between visual homeostatic plasticity and sleep in adult humans.

Sleep and plasticity are highly interrelated, as sleep slow oscillations and sleep spindles are associated with consolidation of Hebbian-based processes. However, in adult humans, visual cortical plasticity is mainly sustained by homeostatic mechanisms, for which the role of sleep is still largely unknown. Here, we demonstrate that non-REM sleep stabilizes homeostatic plasticity of ocular dominance induced in adult humans by short-term monocular deprivation: the counterintuitive and otherwise transient boost of the deprived eye was preserved at the morning awakening (>6 hr after deprivation). Subjects exhibiting a stronger boost of the deprived eye after sleep had increased sleep spindle density in frontopolar electrodes, suggesting the involvement of distributed processes. Crucially, the individual susceptibility to visual homeostatic plasticity soon after deprivation correlated with the changes in sleep slow oscillations and spindle power in occipital sites, consistent with a modulation in early occipital visual cortex.

A new method for precise oscillatory phase targeting affects slow waves and sleep spindles on the short and longer term

A new method for precise oscillatory phase targeting affects slow waves and sleep spindles on the short and longer term

Nine-day continuous recording of EEG and 2-hour of high-density EEG under chronic sleep restriction in mice

This work provides an EEG dataset collected from nine mice during the sleep deprivation (SD) paradigm for the sleep science community. It includes 9-day of continuous recording of the frontal and parietal EEG, accelerometer, and 2-hour of high-density EEG (HD-EEG) under SD and SD-free conditions. Eighteen hours of SD were conducted on 5 consecutive days. The HD-EEG data were saved in the EEGLAB format and stored as the brain imaging data structure (BIDS). These datasets can be used to (i) compare mouse HD-EEG to human HD-EEG, (ii) track oscillatory activities of the sleep EEG (e.g., slow waves, spindles) across the cortical regions under different conditions of sleep pressure, and (iii) investigate the cortical traveling waves in the mouse brain. We also provided Python code for basic analyses of this dataset, including the detection of slow waves and sleep spindles. We hope that our dataset will reveal hidden activities during sleep and lead to a better understanding of the functions and mechanisms of sleep.

Brain states in freely behaving marmosets.

Study ObjectivesWe evaluated common marmosets as a perspective animal model to study human sleep and wake states.MethodsUsing wireless neurologger recordings, we performed longitudinal multichannel local field potential (LFP) cortical, hippocampal, neck muscle, and video recordings in three freely behaving marmosets. The brain states were formally identified using self-organizing maps.ResultsMarmosets were generally awake during the day with occasional 1–2 naps, and they slept during the night. Major electrographic patterns fall in five clearly distinguished categories: wakefulness, drowsiness, light and deep NREM sleep, and REM. Marmosets typically had 14–16 sleep cycles per night, with either gradually increasing or relatively low, but stable delta power within the cycle. Overall, the delta power decreased throughout the night sleep. Marmosets demonstrated prominent high amplitude somatosensory mu-rhythm (10–15 Hz), accompanied with neocortical ripples, and alternated with occipital alpha rhythm (10–15 Hz). NREM sleep was characterized with the presence of high amplitude slow waves, sleep spindles and ripples in neocortex, and sharp-wave-ripple complexes in CA1. Light and deep stages differed in levels of delta and sigma power and muscle tone. REM sleep was defined with low muscle tone and activated LFP with predominant beta-activity and rare spindle-like or mu-like events.ConclusionsMultiple features of sleep–wake state distribution and electrographic patterns associated with behavioral states in marmosets closely match human states, although marmoset have shorter sleep cycles. This demonstrates that marmosets represent an excellent model to study origin of human electrographical rhythms and brain states.

Cross-Frequency Slow Oscillation-Spindle Coupling in a Biophysically Realistic Thalamocortical Neural Mass Model.

Sleep manifests itself by the spontaneous emergence of characteristic oscillatory rhythms, which often time-lock and are implicated in memory formation. Here, we analyze a neural mass model of the thalamocortical loop in which the cortical node can generate slow oscillations (approximately 1 Hz) while its thalamic component can generate fast sleep spindles of σ-band activity (12–15 Hz). We study the dynamics for different coupling strengths between the thalamic and cortical nodes, for different conductance values of the thalamic node's potassium leak and hyperpolarization-activated cation-nonselective currents, and for different parameter regimes of the cortical node. The latter are listed as follows: (1) a low activity (DOWN) state with noise-induced, transient excursions into a high activity (UP) state, (2) an adaptation induced slow oscillation limit cycle with alternating UP and DOWN states, and (3) a high activity (UP) state with noise-induced, transient excursions into the low activity (DOWN) state. During UP states, thalamic spindling is abolished or reduced. During DOWN states, the thalamic node generates sleep spindles, which in turn can cause DOWN to UP transitions in the cortical node. Consequently, this leads to spindle-induced UP state transitions in parameter regime (1), thalamic spindles induced in some but not all DOWN states in regime (2), and thalamic spindles following UP to DOWN transitions in regime (3). The spindle-induced σ-band activity in the cortical node, however, is typically the strongest during the UP state, which follows a DOWN state “window of opportunity” for spindling. When the cortical node is parametrized in regime (3), the model well explains the interactions between slow oscillations and sleep spindles observed experimentally during Non-Rapid Eye Movement sleep. The model is computationally efficient and can be integrated into large-scale modeling frameworks to study spatial aspects like sleep wave propagation.

The adolescent pattern of sleep spindle development revealed by HD-EEG.

Sleep spindles are developmentally relevant cortical oscillatory patterns; however, they have mostly been studied by considering the entire spindle frequency range (11-15 Hz) without a distinction between the functionally and topographically different slow and fast spindles, using relatively few electrodes and analysing wide age-ranges. Here, we employ high-density night sleep electroencephalography in three age-groups between 12 and 20 years of age (30 females and 30 males) and analyse the adolescent developmental pattern of the four major parameters of slow and fast sleep spindles. Most of our findings corroborate those very few previous studies that also make a distinction between slow and fast spindles in their developmental analysis. We find spindle frequency increasing with age. A spindle density change is not obvious in our study. We confirm the declining tendencies for amplitude and duration, although within narrower, more specific age-windows than previously determined. Spindle frequency seems to be higher in females in the oldest age-group. Based on the pattern of our findings, we suggest that high-density electroencephalography, specifically targeting slow and fast spindle ranges and relatively narrow age-ranges would advance the understanding of both adolescent cortical maturation and development and the functional relevance of sleep spindles in general.

The role of sleep for episodic memory consolidation: Stabilizing or rescuing?

Prior studies suggest a role for sleep in memory consolidation, with specific contributions from slow oscillations and sleep spindles (Rasch & Born, 2013). However, recent studies failed to replicate sleep’s superiority over wake in strengthening memory against interference (Cordi & Rasch, 2021). The goal of the current study is to investigate whether sleep protects newly formed memory from unspecific interference induced by daytime experiences over 24 h, as well as to elucidate the sleep features that are involved. 56 healthy adults were randomly assigned to either the Sleep First or Wake First group. The Sleep First group encoded word pairs at night before sleep, while the Wake First group encoded word pairs in the morning before a day of wakefulness. Memory was tested 30 min, 12 h, and 24 h after encoding for both groups. The Sleep First group performed significantly better 12 h after encoding, replicating prior findings that memory is better after a period of sleep compared to wake. However, after 24 h, the two groups performed similarly. The Wake First group showed a positive correlation between overnight memory improvement and the theta and delta band power during slow wave sleep, an effect not found in the Sleep First group. These correlations suggest the possibility that after a day of waking interference, the brain recruits extra sleep resources to rescue memories from further forgetting. Our results are not consistent with prior studies showing a significant role for sleep in stabilizing memory from future interference, but they may suggest that sleep rescues memories after interference has occurred.

P 87 Slow wave sleep of a 90-minute nap relates to hippocampus-dependent spatial memory consolidation

Introduction : The hippocampus is critical for learning and consolidation of behaviourally-relevant spatial information. During spatial learning, spatially-related firing patterns of hippocampal place cells reflecting the subjects‘ location can be detected. It is widely acknowledged that the stabilization of newly encoded memory traces during active system consolidation is promoted by post-learning slow wave sleep (SWS). Here, hippocampal neural sequences are reactivated (“replay”) accompanied by neocortical slow oscillations thereby synchronizing spindle-ripple events originating from hippocampal and thalamic regions. Studies in rodents and humans reported a facilitation of spatial memories after full nights of sleep, in particular in early sleep SWS (i.e., sharp-wave ripples and slow waves). In this ongoing study, we investigated the effect of a 90-min nap on sleep-associated memory consolidation of spatial information. The advantage of an isolated nap condition is the possibility to selectively study the effect of SWS on memory consolidation. Patients & Methods: Forty healthy students between 21 and 32 years were divided into a sleep group (24±1,64 years, 55% female) and a wake group (24±2,68 years, 55% female). For testing spatial learning, the Virtual Water Maze (VWM), a digitalised version of the established Morris Water Maze Test for hippocampus-dependent place learning was used. Here, students had to find a treasure box hidden in the same position on a virtual island. Between learning and the recall sessions of the VWM (90 minutes), students either performed a mid-day nap accompanied by polysomnography (sleep condition) or watched emotionally neutral documentaries (wake condition). The improvement in the recall session was then compared between the groups and the influence of EEG sleep measures was analysed. Results: We found a significant positive correlation between spatial memory consolidation and time spent in SWS (SWS [min]: r=0,612, p=0,004). Accordingly, there was a tendency of a stronger consolidation when amounts of slow oscillations and sleep spindles were higher. When directly compared, there was no significant difference in the various consolidation measures of VWM between the groups . Conclusion: We found that consolidation of hippocampus-dependent spatial memory in a young healthy population was related to longer time spent in SWS as well as the amount of sleep spindles and slow oscillations during NonREM sleep of a 90-minute nap. Our data support the notion that the efficacy of hippocampus-dependent spatial memory consolidation depends on the duration of SWS.

Slow oscillation-spindle coupling strength predicts real-life gross-motor learning in adolescents and adults.

Previously, we demonstrated that precise temporal coordination between slow oscillations (SOs) and sleep spindles indexes declarative memory network development (Hahn et al., 2020). However, it is unclear whether these findings in the declarative memory domain also apply in the motor memory domain. Here, we compared adolescents and adults learning juggling, a real-life gross-motor task. Juggling performance was impacted by sleep and time of day effects. Critically, we found that improved task proficiency after sleep lead to an attenuation of the learning curve, suggesting a dynamic juggling learning process. We employed individualized cross-frequency coupling analyses to reduce inter- and intragroup variability of oscillatory features. Advancing our previous findings, we identified a more precise SO-spindle coupling in adults compared to adolescents. Importantly, coupling precision over motor areas predicted overnight changes in task proficiency and learning curve, indicating that SO-spindle coupling relates to the dynamic motor learning process. Our results provide first evidence that regionally specific, precisely coupled sleep oscillations support gross-motor learning.

Sleep Biomarkers Help Predict the Development of Alzheimer Disease.

Middle-aged or older adults who self-report sleep-wake disorders are at an increased risk for incident dementia, mild cognitive impairment, and Alzheimer disease. Dementia in people with mild cognitive impairment and Alzheimer disease who complain of sleep-wake disorders progress faster than those without sleep-wake disorders. Removal of amyloid-beta and tau tangles occurs preferentially in non-rapid eye movement 3 sleep and fragmented or insufficient sleep may lead to accumulation of these neurotoxins even in preclinical stages. Selective atrophy in the medial temporal lobe on brain MRI has been shown to predict impaired coupling of slow oscillations and sleep spindles. Impaired slow wave-spindle coupling has been shown to correlate with impaired overnight memory consolidation. Whereas, a decrease in the amplitude of 0.6 to 1 Hz slow wave activity predicts higher cortical Aβ burden on amyloid PET scans. Overexpression of the wake-promoting neurotransmitter orexin may predispose patients with mild cognitive impairment and Alzheimer disease to increased wakefulness, decreasing time they need to clear from the brain the neurotoxic accumulation of amyloid-beta and especially tau. More research exploring these relationships is needed and continuing.

Improvements in cognitive function and quantitative sleep electroencephalogram in obstructive sleep apnea after six months of continuous positive airway pressure treatment.

Study ObjectivesUntreated obstructive sleep apnea (OSA) is associated with cognitive deficits and altered brain electrophysiology. We evaluated the effect of continuous positive airway pressure (CPAP) treatment on quantitative sleep electroencephalogram (EEG) measures and cognitive function.MethodsWe studied 167 patients with OSA (age 50 ± 13, AHI 35.0 ± 26.8) before and after 6 months of CPAP. Cognitive tests assessed working memory, sustained attention, visuospatial scanning, and executive function. All participants underwent overnight polysomnography at baseline and after CPAP. Power spectral analysis was performed on EEG data (C3-M2) in a sub-set of 90 participants. Relative delta EEG power and sigma power in NREM and EEG slowing in REM were calculated. Spindle densities (events/min) in N2 were also derived using automated spindle event detection. All outcomes were analysed as change from baseline.ResultsCognitive function across all cognitive domains improved after six months of CPAP. In our sub-set, increased relative delta power (p < .0001) and reduced sigma power (p = .001) during NREM were observed after the 6-month treatment period. Overall, fast and slow sleep spindle densities during N2 were increased after treatment.ConclusionsCognitive performance was improved and sleep EEG features were enhanced when assessing the effects of CPAP. These findings suggest the reversibility of cognitive deficits and altered brain electrophysiology observed in untreated OSA following six months of treatment.

Slow waves contribute to memory consolidation only in older adults without sleep‐disordered breathing

AbstractBackgroundSleep‐dependent memory consolidation, which is thought to rely on the dialogue between the hippocampus and the medial prefrontal cortex (mPFC) during NREM sleep, is mediated by slow waves (SW) and sleep spindles. Some studies indicate that this process is impaired in ageing but also in sleep‐disordered breathing (SDB), a very common sleep disorder in ageing. In this study, we investigated sleep‐dependent memory consolidation in older adults with or without SDB and explored the underlying mechanisms.MethodBaseline data of 57 cognitively unimpaired older adults (mean age ± SD: 68.6 ± 3.3 years) from the Age‐Well cohort were analysed. Participants underwent a structural MRI scan to obtain mPFC and hippocampal grey matter volumes, and performed a visuospatial memory task until reaching a learning criterion of 66.6% of correct answers. Post‐learning sleep was monitored using polysomnography, and delayed recall was probed the next morning. An overnight change in memory performance (OCMP) was computed as follows: (recall performance – learning performance) / learning performance. SW, slow and fast spindles during N2 and N3 sleep were automatically detected using the SleepTrip toolbox. Based on the standard apnea‐hypopnea index (AHI) cutoff of 15 events/h, participants were classified as having SDB (SDB+, n=47) or not (SDB‐, n=10).ResultThere was no between‐group difference in OCMP, as well as in amplitude, duration and frequency of SW, slow and fast spindles (p&gt;0.05). However, we found a significant group by SW density interaction after controlling for age, sex, education, total sleep time and trait‐anxiety (p=0.03). Thus, a positive association was only found between SW density and OCMP in the SDB‐ group (p=0.02; Fig 1). No correlation was found between slow or fast spindle density and OCMP in either group. Finally, mPFC and hippocampal volumes did not differ between SDB+ and SDB‐ participants (p&gt;0.05), but SW density positively correlated with the volume of the mPFC (p=0.01; Fig 2).ConclusionOur findings suggest that the contribution of SW to sleep‐dependent memory consolidation is impaired in participants with SDB and incriminate the mPFC. We plan to conduct connectivity and SW‐spindle coupling analyses to unravel the functional substrates of this deficit.

Nonrapid eye movement sleep characteristics and relations with motor, memory, and cognitive ability from infancy to preadolescence.

Sleep plays a critical role in neural neurodevelopment. Hallmarks of sleep reflected in the electroencephalogram during nonrapid eye movement (NREM) sleep are associated with learning processes, cognitive ability, memory, and motor functioning. Research in adults is well-established; however, the role of NREM sleep in childhood is less clear. Growing evidence suggests the importance of two NREM sleep features: slow-wave activity and sleep spindles. These features may be critical for understanding maturational change and the functional role of sleep during development. Here, we review the literature on NREM sleep from infancy to preadolescence to provide insight into the network dynamics of the developing brain. The reviewed findings show distinct relations between topographical and maturational aspects of slow waves and sleep spindles; however, the direction and consistency of these relationships vary, and associations with cognitive ability remain unclear. Future research investigating the role of NREM sleep and development would benefit from longitudinal approaches, increased control for circadian and homeostatic influences, and in early childhood, studies recording daytime naps and overnight sleep to yield increased precision for detecting age-related change. Such evidence could help explicate the role of NREM sleep and provide putative physiological markers of neurodevelopment.

P143 Sleep-dependent declarative memory consolidation and NREM sleep EEG oscillations in older adults with obstructive sleep apnea

Abstract Objectives To compare overnight declarative memory consolidation and NREM sleep EEG oscillations in older adults with OSA to an age-matched control group, and to assess the quantitative sleep EEG features as correlates of memory consolidation. Methods 46 participants (24 without OSA and 22 patients with OSA) were recruited. Participants completed a word-paired associates declarative memory task before and after an 8-hour sleep opportunity with full polysomnography. Power spectral analysis was performed on all-night EEG recorded at frontal and central electrode sites. We calculated slow wave activity (slow oscillations absolute power 0.25–1 Hz; and delta EEG power (0.5–4.5 Hz) in NREM sleep. Slow spindle density (11–13 Hz, events p/min) and fast spindle density (13–16 Hz, events p/min) in stage N2 was derived using an automated spindle detection algorithm. Results Patients with OSA showed no significant differences in overnight memory recall and recognition compared to individuals without OSA. The OSA group showed reduced slow spindle density at the central region and fast spindle density at the frontal region relative to controls. No differences were observed in SWA. Within group correlations showed slow and fast spindle density were correlated to percent recognition in the control group. Conclusion Older adults with OSA had deficits in slow and fast sleep spindles compared to controls. OSA patients showed preserved sleep-dependent declarative memory consolidation despite sleep fragmentation and intermittent hypoxemia. Sleep spindles were positively correlated with overnight memory consolidation in controls but not OSA patients. Targeted interventions to boost spindles may enhance memory consolidation in older adults.